Career Prospects For Computer Science Graduates By 2023-24
Munish Sabharwal, Professor, Chandigarh University
As per the report by Aspiring Minds, a New Delhi based employment solutions company, as many as 97 percent of graduating engineers want jobs either in software engineering or core engineering. The findings of the same study shows that, out of 100 only 3 per cent of computer science and engineering graduates have suitable skills to be employed in the software or product market and only 7 percent can handle core engineering tasks. Therefore, future job prospects in computer science need a lot of investigation because it is also one of the largest talent absorber in our country.
The days of computer science jobs being centered only around 'Programming Skills' alone have passed, the majority of jobs in computer science by 2022-24 will be centered around 'DATA' because we are knowingly or unknowingly generating a lot of data via search engines, mails, chat messengers, video calls, online transactions, social media, RFID's, IoT, geo tags, and downloads. The world currently generates 2.5 quintillion bytes of data per day. As the world steadily becomes more connected with an ever-increasing number of electronic devices as well as growth of over 7.5% in internet population, data is only set to grow over the coming years. This fact was also accentuated by Mukesh Ambani, Chairman RIL in his famous statement 'Data is the new Oil'. This data that we are generating needs to be warehoused, secured and analyzed to generate insights that can be exploited. Therefore, the CSE jobs of the near future will be centered on data and will fall into four categories. First, the Analysis of Data (Data Science Domain), second, the Security of Data (Data & Cyber Security Domain), third, the Management and Integration of Data (Database Management & Integration Domain) and fourth, the analytical applications of data from interdisciplinary fields (this involves newer interdisciplinary domains like Business, Clinical and Medical Science, Computational Biology, Bioinformatics, Biomedical Engineering etc.). The other major emerging job generation areas in computer science could possibly be AI, Virtual and Augmented Reality, Mobile computing and Mobile Development, Computer Gaming etc. Because of this, there is an urgent need to align academic programs with future employment needs. The brief description of the different computer science domains, their sub domains as well as the career opportunities are encapsulated further.
Data Science is a data-driven science of scientific methods, processes, and systems to extract knowledge from data in various forms. This is a deep investigation of large data sources, and often creating and training systems to recognize patterns in them. Its sub domains are Data Visualization, Data Mining, Predictive and Prescriptive Modeling and Analysis, Data Analytics, Computational Science, Pattern Recognition, Machine Learning, Deep Learning, Big Data and Big Data Analytics etc. The career opportunities in Data Science include Data Scientist, Data Analyst for Predictive and Prescriptive Modeling and Analysis for Businesses, Data Mining Specialists, Big Data Analyst and Algorithm Specialists for Machine Learning.
Data Security, also known as information security or computer security is all of the practices and processes that are in place to ensure data isn't being used or accessed by unauthorized individuals or parties. It refers to protective digital privacy measures that are applied to prevent unauthorized access to computers, databases and websites. It also includes cyber security, which is the protection of systems, networks and data in cyberspace and it is a critical issue for all businesses. Its sub domains are Applied Cryptography, Secured Network Protocols, Network Programming, Ethical Hacking, IOT, Block chain Technology and its Applications etc. The career opportunities in Data Security include software security engineer, Security Analyst, Security consultant, Chief Information Security officer, Security Architect, Computer Forensic Expert, Malware Expert, Ethical Hacker and Network Security Administrator.
"As the world steadily becomes more connected with an ever-increasing number of electronic devices as well as growth of over 7.5% in internet population, data is only set to grow over the coming years"
Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users. Data integration involves combining data from several sources, which are stored using various technologies and provide a unified view of the data. Data Management and Integration involves Data warehousing, RDBMS and No-SQL Databases etc. Its sub domains are Data Warehousing, Data Integration, Database Tuning, Big Data Databases, Distributed Systems, Cloud Computing, Storage Area Networks etc.
The career opportunities in Data Management and Integration include DBA, Data Integration Specialist, Data Warehouse Architect, Senior Data Specialist, Data Analyst, SQL Developer, SQL Programmer and No-SQL Technologies Programmer.
The analytical applications of data from interdisciplinary fields include the data from various different domains, for example Business, Clinical and Medical Science as well as an area such as Biology, which gives rise to application areas like Computational Biology, Bioinformatics, Biomedical Engineering etc to gain better insights and develop newer products and services.
The career opportunities in AI are Research scientists and engineering consultants, Computer scientists and computer engineers, Software analysts and developers, Programmer.
The other AI application areas are Natural Language Processing, Soft Computing, Video Gaming, Manufacturing and electrical engineers, Surgical technicians working with robotic tools, Military and aviation electricians working with flight simulators, drones, and armaments, Robotics and Neural prosthetics, to design equipment's with embedded systems which can act friendly with human brain.
The career opportunities in VR & AR are AR/VR Developer, AR/VR Engineer, AR/VR Architect, Digital Strategy and Transformation Consultant, 3D Architect etc.
A report by the Institute for the Future (IFTF) and a panel of 20 experts from technology, business and academia from around the world and estimated by Dell Technologies, published in the Huffington Post on June 15th 2017 says that things are about to get a lot faster and so fast, in fact that 85% of jobs that will exist in 2030 haven't been invented yet.
We must get ready for the very nature of work to change and also get ready for a lifetime of skills training and retraining in real time. The ability to gain new knowledge will be more valuable than the knowledge itself.
Munish Sabharwal, Professor, Chandigarh University
Dr. Munish Sabharwal is Professor and Associate Dean, Department of Computer Science & Engineering and Adjunct Professor- Faculty of Applied Mathematics and IT-Samarkand State University, Samarkand, Uzbekistan. He has PhD in (CS), PhD in (Management [MIS]) and has been contributing over 21+ years in Teaching (CS and MIS), Education Management, Research as well as S/W Development. Currently spearheading efforts as Professor &Associate Dean (CSE), Chandigarh University, Mohali (Punjab) INDIA. His current research interests include Data Science AI& ML, Biometrics & E-Banking.
The days of computer science jobs being centered only around 'Programming Skills' alone have passed, the majority of jobs in computer science by 2022-24 will be centered around 'DATA' because we are knowingly or unknowingly generating a lot of data via search engines, mails, chat messengers, video calls, online transactions, social media, RFID's, IoT, geo tags, and downloads. The world currently generates 2.5 quintillion bytes of data per day. As the world steadily becomes more connected with an ever-increasing number of electronic devices as well as growth of over 7.5% in internet population, data is only set to grow over the coming years. This fact was also accentuated by Mukesh Ambani, Chairman RIL in his famous statement 'Data is the new Oil'. This data that we are generating needs to be warehoused, secured and analyzed to generate insights that can be exploited. Therefore, the CSE jobs of the near future will be centered on data and will fall into four categories. First, the Analysis of Data (Data Science Domain), second, the Security of Data (Data & Cyber Security Domain), third, the Management and Integration of Data (Database Management & Integration Domain) and fourth, the analytical applications of data from interdisciplinary fields (this involves newer interdisciplinary domains like Business, Clinical and Medical Science, Computational Biology, Bioinformatics, Biomedical Engineering etc.). The other major emerging job generation areas in computer science could possibly be AI, Virtual and Augmented Reality, Mobile computing and Mobile Development, Computer Gaming etc. Because of this, there is an urgent need to align academic programs with future employment needs. The brief description of the different computer science domains, their sub domains as well as the career opportunities are encapsulated further.
Data Science is a data-driven science of scientific methods, processes, and systems to extract knowledge from data in various forms. This is a deep investigation of large data sources, and often creating and training systems to recognize patterns in them. Its sub domains are Data Visualization, Data Mining, Predictive and Prescriptive Modeling and Analysis, Data Analytics, Computational Science, Pattern Recognition, Machine Learning, Deep Learning, Big Data and Big Data Analytics etc. The career opportunities in Data Science include Data Scientist, Data Analyst for Predictive and Prescriptive Modeling and Analysis for Businesses, Data Mining Specialists, Big Data Analyst and Algorithm Specialists for Machine Learning.
Data Security, also known as information security or computer security is all of the practices and processes that are in place to ensure data isn't being used or accessed by unauthorized individuals or parties. It refers to protective digital privacy measures that are applied to prevent unauthorized access to computers, databases and websites. It also includes cyber security, which is the protection of systems, networks and data in cyberspace and it is a critical issue for all businesses. Its sub domains are Applied Cryptography, Secured Network Protocols, Network Programming, Ethical Hacking, IOT, Block chain Technology and its Applications etc. The career opportunities in Data Security include software security engineer, Security Analyst, Security consultant, Chief Information Security officer, Security Architect, Computer Forensic Expert, Malware Expert, Ethical Hacker and Network Security Administrator.
"As the world steadily becomes more connected with an ever-increasing number of electronic devices as well as growth of over 7.5% in internet population, data is only set to grow over the coming years"
Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users. Data integration involves combining data from several sources, which are stored using various technologies and provide a unified view of the data. Data Management and Integration involves Data warehousing, RDBMS and No-SQL Databases etc. Its sub domains are Data Warehousing, Data Integration, Database Tuning, Big Data Databases, Distributed Systems, Cloud Computing, Storage Area Networks etc.
The career opportunities in Data Management and Integration include DBA, Data Integration Specialist, Data Warehouse Architect, Senior Data Specialist, Data Analyst, SQL Developer, SQL Programmer and No-SQL Technologies Programmer.
The analytical applications of data from interdisciplinary fields include the data from various different domains, for example Business, Clinical and Medical Science as well as an area such as Biology, which gives rise to application areas like Computational Biology, Bioinformatics, Biomedical Engineering etc to gain better insights and develop newer products and services.
The career opportunities in AI are Research scientists and engineering consultants, Computer scientists and computer engineers, Software analysts and developers, Programmer.
The other AI application areas are Natural Language Processing, Soft Computing, Video Gaming, Manufacturing and electrical engineers, Surgical technicians working with robotic tools, Military and aviation electricians working with flight simulators, drones, and armaments, Robotics and Neural prosthetics, to design equipment's with embedded systems which can act friendly with human brain.
The career opportunities in VR & AR are AR/VR Developer, AR/VR Engineer, AR/VR Architect, Digital Strategy and Transformation Consultant, 3D Architect etc.
A report by the Institute for the Future (IFTF) and a panel of 20 experts from technology, business and academia from around the world and estimated by Dell Technologies, published in the Huffington Post on June 15th 2017 says that things are about to get a lot faster and so fast, in fact that 85% of jobs that will exist in 2030 haven't been invented yet.
We must get ready for the very nature of work to change and also get ready for a lifetime of skills training and retraining in real time. The ability to gain new knowledge will be more valuable than the knowledge itself.
Munish Sabharwal, Professor, Chandigarh University
Dr. Munish Sabharwal is Professor and Associate Dean, Department of Computer Science & Engineering and Adjunct Professor- Faculty of Applied Mathematics and IT-Samarkand State University, Samarkand, Uzbekistan. He has PhD in (CS), PhD in (Management [MIS]) and has been contributing over 21+ years in Teaching (CS and MIS), Education Management, Research as well as S/W Development. Currently spearheading efforts as Professor &Associate Dean (CSE), Chandigarh University, Mohali (Punjab) INDIA. His current research interests include Data Science AI& ML, Biometrics & E-Banking.
